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</p><p>Title Page i <br>Declaration ii <br>Certification iii<br>Dedication iv<br>Acknowledgement v<br>Table of Contents vii<br>List of Figures x<br>List of Tables xi<br>List of Plates xiv<br>Abbreviations and Symbols xv<br>Abstract xvi<br> <br><b>
Chapter ONE
: INTRODUCTION</b><br>11 Background Information 1 <br>12 Water Quality modelling 3<br>13 Description of Study Location 5<br>14 Statement of The Problem 6<br>15 Aim 6<br>16 Objectives 6<br>17 Significance of Study 6<br>18 Scope of Study 7<br> <br>
Chapter TWO
: LITERATURE REVIEW<br>21 Water Quality Modelling as a Field of Study 8<br>22 Coefficient of Re-aeration, k2 9<br>223 The Indian k2 Model 13<br>224 The Chilean k2 Model 14<br>225 The Nigerian k2 Model 15<br>23 Water Laws and Standards 15<br>24 Statistical Analysis 17<br>241 Some Relevant Statistical Operations 17<br>242 Statistical Software 19<br>243 Model Calibration and Validation in Water Quality<br>Data 20<br>2431 Sum of Squares Due to Error 21<br>2432 R-Square 21<br>2433 Degrees of Freedom Adjusted R-Square 22<br>2434 Root Mean Squared Error 22<br> <br><b>
Chapter THREE
: METHODOLOGY </b><br> 31 Selection of the Study Area 24<br> 32 Determination of Sampling Stations 27<br> 33 Field Activities 49<br> 331 Field Observations 31<br> 332 Field Sampling Visits 31<br> 3321 Rationale for Gathering Data Once Every Month 32<br> 3322 Activities During the Field Exercises 33<br> 34 Materials 34<br> 3</p><p>5 Laboratory Analysis 36<br> 36 Data Analysis 37<br> 361 Time of Travel 38<br> 362 Re-aeration Coefficient Model 39<br> <br><b>
Chapter FOUR
: DATA PRESENTATION AND INTERPRETATION</b><br> 41 Data Gathering 40<br> 411 Hydraulic Data 41<br> 412 Physico-Chemical Data 50<br> 413 Monthly Variations in DO, Temperature, Stream Depth 57<br> 42 Computation of Measured k2 63<br> 43 Re-arrangement of Sampling Stations 67<br>431 Time of Travel 68<br>432 Hydraulic Radius 80<br>433 Ultimate BOD and De-oxygenation Rate 80<br>434 Saturation DO and the Upstream and Downstream DO deficits 80<br> 435 Determination of k2 80<br>436 Model Parameters 80<br>437 The Model 83<br>438 Comparison with other Selected Models 83<br>44 Water Use Practices 103<br> 45 Pollutants and Public Health Implications 106<br> <br><b>
Chapter FIVE
: CONCLUSION AND RECOMMENDATION</b><br>51 Conclusion 110<br>52 Contribution to Knowledge 111<br>53 Recommendations 111<br> <br><b>REFERENCES 113<br> <br>APPENDICES </b><br>Appendix 1: Matlab Code for Beta 121<br>Appendix 2: Matlab Model Output 128<br>Appendix 3: Matlab Code and Output for Plot of all Models 132<br>Appendix 4: Mix Calculations 140<br>Appendix 5: Laboratory Reports 147 <br>Appendix 6: Procedure for data Analysis 160</p><p><b><br>LIST OF FIGURES PAGE</b><br>Figure 11 – Nigerian Household distribution by source of water supply 2<br>Figure 12 – Nigerian Household distribution by Toilet Facilities 3<br>Figure 13 â“ General Layout of the Study area 5<br>Figure 31â“ Field Sampling Stations 28<br>Figure 32 â“ Linear representation of Sampling Points 29<br>Figure 33 – Sampling Cross-section 33<br>Figure 41 â“ An 8-month mean stream velocity record 59<br>Figure 42 â“ An 8-month mean ambient temperature record 60<br>Figure 43 â“ An 8-month mean water temperature record 61<br>Figure 44 â“ An 8-month mean stream depth record 61<br>Figure 45 â“ DO Fluctuations over an 8-month period 62<br>Figure 46 – Flowchart showing the progression of the statistical analysis 86<br>Figure 47 â“ Plot of 11 models using January data 93<br>Figure 48 â“ Plot of measured k2 against computed k2 using January data 94<br>Figure 49 â“ Plot of 11 models using March data 96<br>Figure 410 – Plot of measured k2 against computed k2 using March data 97<br>Figure 411 â“ Plot of 11 models using July data 99<br>Figure 412 – Plot of measured k2 against computed k2 using July data 100<br><b><br>LIST OF TABLES PAGE</b><br> <br>Table 21 â“ The self-purification factor, f, of different water bodies at 20oC 9<br>Table 22 â“ Solubility of Oxygen in water 10<br>Table 31 – Details of Sampling Stations 30<br>Table 32 â“ Parameters Measured with Relevance to study 32<br>Table 33 â“ Parameters, equipment and Processes of parameter determination<br>Schedule for field work 34<br>Table 41 – Sampling dates and conditions 40<br>Table 42a â“ Hydraulic Data for January 42<br>Table 42b â“ Hydraulic Data for February 43<br>Table 42c â“ Hydraulic Data for March 44<br>Table 42d â“ Hydraulic Data for April 45<br>Table 42e â“ Hydraulic Data for May 46<br>Table 42f â“ Hydraulic Data for July 47<br>Table 42g â“ Hydraulic Data for August 48<br>Table 42h â“ Hydraulic Data for September 49<br>Table 43a â“ Physico-Chemical Parameters for January 50<br>Table 43b â“ Physico-Chemical Parameters for February 51<br>Table 43c â“ Physico-Chemical Parameters for March 52<br>Table 43d â“ Physico-Chemical Parameters for April 53<br>Table 43e â“ Physico-Chemical Parameters for May 54<br>Table 43f â“ Physico-Chemical Parameters for July 55<br>Table 43g â“ Physico-Chemical Parameters for August 56<br>Table 43hâ“ Physico-Chemical Parameters for September 57<br>Table 44 â“ Mean Monthly Ambient and Water Temperatures 60<br>Table 45 â“ Determination of Reaches for the River 64<br>Table 46 – Dilution Effects for January 65<br>Table 47 – Dilution Effects for February 65<br>Table 48 – Dilution Effects for March 65<br>Table 49 – Dilution Effects for July 66<br>Table 410 – Dilution Effects for August 66<br>Table 411 – Dilution Effects for September 66<br>Table 412 â“ Re-arrangement of station numbers 67<br>Table 413 â“ Computation of time of travel on Programmed Excel Spreadsheet for January 68<br>Table 414 â“ Computation of time of travel on Programmed Excel Spreadsheet for<br>February 69<br>Table 415 â“ Computation of time of travel on Programmed Excel Spreadsheet for<br>March 70<br>Table 416 â“ Computation of time of travel on Programmed Excel Spreadsheet for<br>July 71<br>Table 417 â“ Computation of time of travel on Programmed Excel Spreadsheet for<br>August 72<br>Table 418 â“ Computation of time of travel on Programmed Excel Spreadsheet for<br>September 73<br>Table 419 â“ Computation of k1 and k2 on Programmed Excel Spreadsheet for JanuaryTable 420 â“ Computation of k1 and k2 on Programmed Excel Spreadsheet for<br>February 75<br>Table 421 â“ Computation of k1 and k2 on Programmed Excel Spreadsheet for March<br> 76<br>Table 422â“ Computation of k1 and k2 on Programmed Excel Spreadsheet for July<br> 77<br>Table 423 â“ Computation of k1 and k2 on Programmed Excel Spreadsheet for August<br> 78<br>Table 424 â“ Computation of k1 and k2 on Programmed Excel Spreadsheet for<br>September 79<br>Table 425â“ Model fit and goodness of fit Summary for Dry Season 81<br>Table 426â“ Model fit and goodness of fit Summary for Rainy Season 82<br>Table 427 â“ Selected Models for Model Validation (Test of performance) 84<br>Table 428â“ Goodness of fit using January Data 91<br>Table 429- Goodness of fit using March Data 91<br>Table 430- Goodness of fit using July Data 92<br>Table 431: Graphical Goodness of fit using January, March and July Data 102<br>Table 432 â“ Order of Composite Goodness of Fit 103<br>Table 433 â“ Comprehensive River water and Industrial Effluent Analysis 107<br>LIST OF PLATES PAGE<br>Plate 31 â“ The industrial effluent flowing along the road down towards the river 25<br>Plate 32 â“ the effluent accumulates (left) from where it seeps into the river body 25<br>Plate 33 â“ Effluent accumulation beside the river body 26<br>Plate 34 â“ Villagers of Iju tapping the river water for domestic use 26<br>Plate 35 â“ Sewage being taken near the river for disposal 27<br>Plate 36 â“ Field pH meter 35<br>Plate 37 â“ Eurolab digital thermometer with sensitive probe 35<br>Plate 38 – Geopacks Stream flow sensor with its pole and fan-like impeller 36<br>Plate 39 – Measuring the river width with a tape 36<br>Plate 310 â“ the Speedtech Portable Depth Sounder (yellow torchlight shaped<br>instrument) 57<br>Plate 41 â“ Sampling Station 10 in Rainy season (August) 58<br>Plate 42 â“ Sampling Location 10 in Dry season (March) 58<br>Plate 43 â“ Human skeleton found in the River 104<br>Plate 44 â“ Pollution along the river channel 104<br>Plate 45 â“ The research team could not proceed because of blockage of the river 105<br>Plate 46 â“ Water intake station for Ogun State Water Corporation 105<br>Plate 47 â“ Man swimming after the dayâs work 106</p><p><b>ABBREVIATIONS AND SYMBOLS</b><br>1 DO â“ Dissolved Oxygen<br>2 BOD – Biochemical Oxygen Demand<br>3 QUAL â“ Stream Water Quality models<br>4 CORMIX â“ Cornell Mixing Zone Expert<br>5 WASP â“ Watershed Quality Analysis Simulation Programme<br>6 FEPA â“ Federal Environmental Protection Agency<br>7 USEPA â“ United States Environmental Protection Agency<br>8 USGS â“ United States Geological Society<br>9 UNESCO â“ United Nations Education, Scientific and Cultural Organization<br>10 DV â“ Dependent Variable<br>11 IV â“ Independent Variable<br>12 ANOVA â“ Analysis of Variance<br>13 SSE â“ Error Sum of Squares<br>14 SSR â“ Residual sum of squares<br>15 SST â“ Total sum of squares<br>16 R2 â“ correlation coefficient<br>17 Adj R2â“ Adjusted Correlation coefficient<br>18 RMSE â“ Root mean square error<br>19 APHA – American Public Health Association<br>20 SPSS â“ Statistical Package for Social Sciences<br>21 MATLAB â“ Matrix Laboratory software<br>22 GPS â“ Global Positioning System<br>23 k2 â“ re-aeration coefficient<br>24 k1 â“ de-oxygenation coefficient<br>25 f â“ self purification factor<br>26 2 ^Ï – estimated variance<br>27 mg/l â“ milligram per litre</p>
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Project Abstract
This study was carried out on River Atuwara in Ota, Ogun State, Nigeria with the aim of developing a coefficient of re-aeration model applicable to River Atuwara and other rivers in the Nigerian environment. This was achieved by sourcing for data once every month from 22 sampling locations of interest within a pre-selected segment of the river over a period covering the dry and wet seasons. The data collected include hydraulic data (depth, width, velocity and time of travel) and water quality data such as Dissolved Oxygen (DO) and Biochemical Oxygen Demand (BOD). Excel Spreadsheet and MATLAB were used for data processing. Regression analysis was carried out where stream velocity and depth were the regressors and the re-aeration constant k2 (as a function of BOD, DO and Temperature) was the dependent variable. A coefficient of re-aeration, k2, (Atuwara re-aeration model) was developed and validated statistically. Its performance was also verified by comparing the model with 10 other internationally recognized models. It was found that even though Atuwara model performed better than Agunwamba model and most of the other well cited models, both Atuwara model and Agunwamba model could be safely adopted for future water quality modelling researches in the Nigerian environment. Results of detailed water analysis of samples from River Atuwara shows high level of pollution hence it is unfit for human consumption without adequate treatment. It is recommended that River Atuwara and similar rivers in the country should be regularly monitored for quality control.